Optimal Chiller Loading Using Genetic Programming

• Main Authors: Ren-Jie Wei, 魏仁杰
• Other Authors: 張永宗
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/7vhwqg

碩士 === 國立臺北科技大學 === 能源與冷凍空調工程系碩士班 === 95 === This study used a algorithm which about creature evolution - Genetic Program. To analyze the consumption energy model of chiller, and to compute the optimal load sharing for multiple chillers by using this algorithm. Must to record the dates which would effect the consumption energy of chiller before to construct the chiller model. The dates include the chiller water supply temperature、cooling water return temperature and refrigeration ton. Finally, taking these dates and using it as the functions of genetic program (GP), and using the standard arithmetic operation as the terminals of GP. The object in this algorithm is the chiller consumption energy. Through the option of GP which contains ‘crossover’、 ‘reproduce’ and ‘mutation’ to iterant compute the population is composed of functions and the terminals of GP. Finally, we would find the consumption energy model of chiller. The consumption energy for central system is relate to the operating efficiency of multiple chillers. The purpose of the Optimal Chiller Loading (OCL) is to meet the system load and to decide the chillers’ optimal part load ratios (PLR) to reduce the system power consumption. The optimal chiller loading methods include Average Loading (AVL) method and Largrangian Multiplier (LGM) method These methods have some shortcomings. Such as AVL method being not optimal. LGM method will diverge if the initial condition isn’t suitable. This thesis uses a square equation to simulate the chiller’s kw-plr curve and to find a set of chiller output which doesn’t violate the operating limits while minimizing the objective function. The GP is adopted to find the near optimal solution of the function.